If you are one of those persons, starting as soon as possible is the best choice. Before anything else, machine learning or ML is about teaching machines how to learn from a set of data. As a result, they can make predictions or decisions. When applied properly, the machines can learn to characterize patterns automatically.
ML sits at the intersection of computer science and statistics. There are many real-world use cases of machine learning that we can find nowadays. As you learn machine learning further, you will realize those spam email detectors and a self-driving car are some of the things that benefit machine learning.
Many business leaders start to recognize the big potential behind machine learning. And some of them are ready to involve this technology in their enterprise. For this reason, understanding machine learning is a great thing to do. But, how can we do t start learning ML? Read on to discover the answer.
Just like many beginners out there, you may wonder whether it is difficult or not to learn ML. Despite the number of machine learning tutorials and well-written textbooks out there, this thing is still considered as a hard issue. However, it doesn’t mean that you cannot learn it.
We cannot deny that the science of advancing ML algorithms through research is hard. It calls for experimentation, creativity, and tenacity. When you learn machine learning for the first time, you may find it hard to implement existing models and algorithms. But believe it, it is a part of learning.
The difficulty is typically not due to math. However, it is often caused by developing an intuition for what tool should be controlled to solve an issue. It requires knowledge of existing models and algorithms as well as the trade-offs and limitations of each one.
However, if you never start, you will never be able to go there. This is because the skill is understood through the exposure of these models. Once you expose yourself with classes, papers, and textbooks related to machine learning algorithms, your skill will begin to develop in time.
Then, how should we do to start learning? The best advice is to adjust your mindset first. There is no doubt that it is something hard to learn, but make yourself believe that you can do it. Believe that you can practice and apply machine learning in the end.
If something is holding you back from learning ML, you should identify and tackle it to make progress. For example, you struggle with a self-limiting belief. At this point, you need to put away any thought that is limiting yourself and believe in your goals.
Many people who want to learn machine learning wait to get started. This is one of the worst approaches. By never starting to learn, you will never accomplish your goals. For example, you wait to understand statistics or other things. In fact, you can get started in machine learning right now!
There are some ways to make it easier. The best advice is to make it fun. You should first gather anything that can encourage you to learn ML. Once you are motivated, start by learning something simple, so you won’t give up easily. After that, you can continue practicing various small projects.
Now, let’s get into more technical details. Before you start, it is important to remember that there are no fixed tracks. This means that you can do everything in your unique way without being to fixated to a step-by-step tutorial. Learn it in your way for better result.
As you learn the basics of machine learning, it will be a good idea to master a programming language. Python is the most popular choices. It is also the most recommended option for beginners since there are many resources to learn it. Learn by doing can be a good idea here.
When you learn machine learning further, you should know how to use Numpy and Scipy for math. These two are mathematical libraries. Moreover, you should learn Pandas as well. It is a python library for data analysis and manipulation. Matplotlib and Seaborn are other libraries that you should learn.
After that, you can read about Scikit-learn, a python library which has many implemented models. You can use them to train and create predictions directly. You can also tune the model’s parameters to go with your problem. Next, you can read about hands-on machine learning with this.
The most essential thing is to be up to date with the latest discoveries in this field. It is recommended to read a selection of papers, follow a range of writers and publications, and reach out to some communities that have the same passion with you.
Another important thing is practicing. At this point, you should learn further about a programming language and master it. Once you understand the basics, you can continue your learning to linear algebra, statistics and probability, and calculus. Consider joining some popular free courses as well.
Furthermore, you can practice a lot on Kaggle. Here, you can solve problems with the techniques that you have understood so far. Then, you can also learn how to work with databases. In the end, you should dedicate your time to practice and have a faith that you can do it.
In conclusion, learning ML can be a hard thing. However, it doesn’t mean that you can’t learn it. By dedicating your time and effort, it won’t be impossible to understand everything. Start with something simple, so you won’t give up easily. That’s all the best ways to learn machine learning.